70% of Business Intelligence projects never make it into production (Source: Gartner – Big Data Project 2024). They do not slow down, they do not get postponed, they do not get resized. They die. And the most convenient explanation is always the same: the technology was not suitable, the data was messy, the integration too complex.
The problem is that this is not true. Or rather, it is not the real issue.
The reality is more uncomfortable to admit: Business Intelligence does not fail because of the platforms, but because of how it is treated by management. It is launched as a promising initiative, often sponsored at the highest levels, only to be abandoned halfway when it stops being a visible priority.
In recent years, technology has made enormous progress. BI platforms are mature, powerful, flexible. The problem is that they are chosen and evaluated as if they were finished solutions, when in fact they are empty infrastructures. They must be filled with models, KPIs, rules, coherent data.
When BI becomes an empty box that consumes time and budget
At this point, external consultants enter the scene. The project expands, workshops are organized, meetings multiply, working groups are created. Every department must contribute, provide data, explain processes, validate numbers. The problem is that the managers involved already have full agendas. BI becomes important, but never urgent. And anything that is not urgent in a company tends to slip.
Meanwhile, data is never truly “ready.” Every system has its own logic, every department its own KPI definition, every Excel file tells a slightly different story. More time is spent discussing whether the number is correct than using it to make decisions. The project slows down, costs increase, complexity grows. And the more complexity grows, the less desire there is to deal with it.
This is where many projects begin to lose internal support because they turn into a problem to manage. No one openly cancels them. They simply stop being defended. And this is the first real sign that the project is entering its slow terminal phase.
Time passes, the context changes, the project fades out
At this stage, the Business Intelligence project is formally still alive, but inside the company something else is already happening. New clients arrive, often larger and more complex. Volumes increase, operational urgencies grow, exceptions multiply. Management attention shifts to what has immediate impact.The problem is not that someone decides to stop the project. The problem is that no one has time to follow it anymore. Calls are postponed, data requests remain unanswered, KPI decisions are delayed. At this point, the project enters a sort of organizational limbo.This is how most Business Intelligence projects die. Not with a spectacular failure, but from lack of attention, lack of energy, lack of continuous sponsorship.
The collateral damage: Excel everywhere, decision silos
When a Business Intelligence project fades out, the company does not stop. It continues with alternative solutions. Each department keeps building its own reports, almost always in Excel. Everyone uses “their” data, “their” definitions, “their” numbers.
Logistics looks at volumes, finance looks at costs, transport looks at shipments. Everyone has numbers, but no one has the same numbers. Meetings turn into exercises in defending data, not moments of decision. More time is spent discussing how a KPI was calculated than deciding what to do tomorrow.
This is exactly the scenario from which B-AI Semplice was born. Not as a technological alternative to large platforms, but as a pragmatic response to a recurring organizational failure. The idea is simple and, for that very reason, unconventional. Drastically reduce the time between decision and use. Eliminate the endless building phase. Remove the excuse of “we are not ready yet.”
B-AI Semplice was created for those working in logistics and transport who need control, not another project to manage. A ready-to-use, vertical BI with preconfigured KPIs, capable of reading both physical and logical warehouses and transport flows wherever they are. Not in a few days, but in a few weeks. Long enough to be credible, short enough to remain a priority.
Because the real problem of Business Intelligence has never been knowing what to do. It has always been being able to do it before the context changes again.